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A robot needs to learn about his body and the environment. It tries a few different motions and uses the algorithm. It can then predict what will happen with larger movements and at higher speeds. Picture: IST Austria, Birgit Rieger.

First machine learning method capable of accurate extrapolation

Scientists develop new machine learning method that can make robots safer - New method provides simpler and more intuitive models of physical situations

Understanding how a robot will react under different conditions is essential to guaranteeing its safe operation. But how do you know what will break a robot without actually damaging it? A new method developed by scientists at the Institute of Science and Technology Austria and the Max Planck Institute for Intelligent Systems is the first machine learning method that can use observations made under safe conditions to make accurate predictions for all possible conditions governed by the same physical dynamics. Especially designed for real-life situations, their method provides simple, interpretable descriptions of the underlying physics. The researchers will present their findings tomorrow at this year’s prestigious International Conference for Machine Learning (ICML).


Maschinelles Lernen Extrapolation Roboter

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Georg Martius
Max Planck Research Group Leader